autointent.metrics.retrieval_precision#
- autointent.metrics.retrieval_precision(query_labels, candidates_labels, k=None)#
Calculate the precision at position k.
Precision at position \(k\) is calculated as:
\[\text{Precision@k} = \frac{1}{N} \sum_{i=1}^N \frac{|y_{\text{query},i} \cap y_{\text{candidates},i}^{(1:k)}|}{k}\]where: - \(N\) is the total number of queries, - \(y_{\text{query},i}\) is the true label for the \(i\)-th query, - \(y_{\text{candidates},i}^{(1:k)}\) is the set of top-k predicted labels for the \(i\)-th query.
- Parameters:
query_labels (autointent.metrics.custom_types.LABELS_VALUE_TYPE) – For each query, this list contains its class labels
candidates_labels (autointent.metrics.custom_types.CANDIDATE_TYPE) – For each query, these lists contain class labels of items ranked by a retrieval model (from most to least relevant)
k (int | None) – Number of top items to consider for each query
- Returns:
Score of the retrieval metric
- Return type: